The present invention generally relates to clinical decision support. More particularly, the presently described technology relates to systems and methods for a clinical decision support crawler agent.
Healthcare facilities, such as hospitals or clinics, include medical information management systems, such as hospital information systems (HIS), radiology information systems (RIS), clinical information systems (CIS), cardiovascular information systems (CVIS), picture archiving and communication systems (PACS), laboratory information systems (LIS), and electronic medical records (EMR). Information stored may include patient medical histories, imaging data, test results, diagnosis information, management information, and/or scheduling information, for example. The information may be centrally stored or divided at a plurality of locations.
One example of a medical information management system is a PACS. PACS connect to medical diagnostic imaging devices and employ an acquisition gateway (between the acquisition device and the PACS), storage and archiving units, display workstations, databases, and sophisticated data processors. These components are integrated together by a communication network and data management system. A PACS has, in general, the overall goals of streamlining healthcare operations, facilitating distributed remote examination and diagnosis, and improving patient care.
A typical application of a PACS system is to provide one or more medical images for examination by a medical professional. For example, a PACS system can provide a series of x-ray images to a display workstation where the images are displayed for a radiologist to perform a diagnostic examination. Based on the presentation of these images, the radiologist can provide a diagnosis. For example, the radiologist can diagnose a tumor or lesion in x-ray images of a patient's lungs.
A reading, such as a radiology or cardiology procedure reading, is a process of a healthcare practitioner, such as a radiologist or a cardiologist, viewing digital images of a patient. The practitioner performs a diagnosis based on the content of the diagnostic images and reports on the results electronically (e.g., using dictation or otherwise) or on paper. The practitioner typically uses other evidence to aid in performing the diagnosis. Some examples of other evidence are prior (e.g., historical) exams and their results, other images, key image notes, laboratory exams and reports (such as blood work), allergies, pathology results, medication, alerts, document images, and other reports. In addition, the practitioner may want to consider other clinical evidence relevant to the context of the diagnosis being made as well as evidence pertaining to family members that may have a genetic link to the patient.
However, with current systems, the healthcare practitioner must manually seek out any additional evidence to be used in performing the diagnosis. That is, current systems do not automatically provide the practitioner with additional, potentially relevant, evidence to be considered.
In addition, relevant evidence may be located in various evidence sources. Evidences sources may include, for example, medical information management systems in different healthcare facilities. The healthcare facilities, such as hospitals and clinics, may be geographically distributed, and potentially even in different countries. For example, a patient may have gone to a hospital while on vacation years prior and had x-rays taken that might be relevant evidence for a healthcare practitioner to consider in making the current diagnosis. As another example, a patient may visit another geographic location or country for a special medical procedure, perhaps for cost or clinical reasons. As another example, a patient may have moved or immigrated from another city, region, state, or country. Current systems do not provide an efficient mechanism to gather evidence from evidence sources such as remote facilities, hospitals, or clinics. That is, current systems do not allow a practitioner to easily access such evidence.
Further, in addition to difficulty in obtaining the evidence, a practitioner must know of the existence of the evidence and where it is located. It is virtually impossible for a practitioner to manually search every possible healthcare facility's medical information management systems to locate potentially relevant evidence. A healthcare practitioner cannot obtain and utilize evidence he does not know about.
Clinical decision support systems provide assistance to healthcare providers such as physicians. A clinical decision support system may be part of a CIS, HIS, and/or PACS, for example. For example, a clinical decision support system in a PACS can aid a physician in making decisions regarding diagnosis and/or treatment. A clinical decision support system is particularly useful for aiding a healthcare practitioner in situations beyond the context of the practitioner's experience. A clinical decision support system may provide a recommendation for diagnosis and/or treatment. The recommendation may be based on one or more pieces of evidence provided to the clinical decision support system. As is true for a healthcare provider, a clinical decision support system can provide a better recommendation when more evidence is available to be considered.
Thus, there is a need for a healthcare practitioner to be able to locate and obtain access to evidence from multiple evidence sources. Further, there is a need for a clinical decision crawler agent to aid the practitioner to locate and obtain evidence for diagnosis and/or treatment and to make a recommendation based on the obtained evidence.